class_docstr: Latent Variables Class
  
  Holds latent variable objects and contains method for latent variable manipulation. Latent variables are 
  referred to as z as shorthand. This is convention in much of the literature.
docstr: Adjusts priors for the latent variables
  
  Parameters
  ----------
  index : int or list[int]
      Which latent variable index/indices to be altered
  
  prior : Prior object
      Which prior distribution? E.g. Normal(0,1)
  
  Returns
  ----------
  None (changes priors in Parameters object)
docstr_tok: ["Adjusts","priors","for","the","latent","variables","Parameters","--","--","--","--","--","index",":","int","or","list","[","int","]","Which","latent","variable","index\/indices","to","be","altered","prior",":","Prior","object","Which","prior","distribution","?","E.g",".","Normal","(","0,1",")","Returns","--","--","--","--","--","None","(","changes","priors","in","Parameters","object",")"]
code: def adjust_prior(self, index, prior):
      """Adjusts priors for the latent variables
  
      Parameters
      ----------
      index : int or list[int]
          Which latent variable index/indices to be altered
  
      prior : Prior object
          Which prior distribution? E.g. Normal(0,1)
  
      Returns
      ----------
      None (changes priors in Parameters object)
      """
  
      if isinstance(index, list):
          for item in index:
              if (
                  item < 0
                  or item > (len(self.z_list) - 1)
                  or not isinstance(item, int)
              ):
                  raise ValueError(
                      "Oops - the latent variable index "
                      + str(item)
                      + " you have entered is invalid!"
                  )
              else:
                  self.z_list[item].prior = prior
                  if hasattr(self.z_list[item].prior, "mu0"):
                      self.z_list[item].start = self.z_list[
                          item
                      ].prior.mu0
                  elif hasattr(self.z_list[item].prior, "loc0"):
                      self.z_list[item].start = self.z_list[
                          item
                      ].prior.loc0
      else:
          if (
              index < 0
              or index > (len(self.z_list) - 1)
              or not isinstance(index, int)
          ):
              raise ValueError(
                  "Oops - the latent variable index "
                  + str(index)
                  + " you have entered is invalid!"
              )
          else:
              self.z_list[index].prior = prior
              if hasattr(self.z_list[index].prior, "mu0"):
                  self.z_list[index].start = self.z_list[
                      index
                  ].prior.mu0
              elif hasattr(self.z_list[index].prior, "loc0"):
                  self.z_list[index].start = self.z_list[
                      index
                  ].prior.loc0
  
imports: import numpy
  import pandas
  from .covariances import acf
  from .output import TablePrinter
  from .inference import *
  from .families import Normal, t, TruncatedNormal, Cauchy, Skewt, InverseGamma, Flat, InverseWishart, Laplace
label_desc: Use image node_id 5 for calling the LatentVariables obj's underlying member method code with example usage: obj.adjust_prior(index, prior) without return types